Lens undistortion and image rectification is a commonly used pre-processing, e.g. for active or passive stereo vision to reduce the complexity of the search for matching points. The undistortion and rectification is implemented in a field programmable gate array (FPGA). The algorithm is performed pixel by pixel. The challenges of the implementation are the synchronisation of the data streams and the limited memory bandwidth. Due to the memory constraints, the algorithm utilises a pre-computed lossy compression of the rectification maps by a ratio of eight. The compressed maps occupy less space by ignoring the pixel indexes, sub-sampling both maps, and reducing repeated information in a row by forming differences to adjacent pixels. Undistorted and rectified images are calculated once without and once with the compressed transformation map. The deviation between the different computed images is minimal and negligible. The functionality of the hardware module, the decompression algorithm and the processing pipeline are described. The algorithm is validated on a Xilinx Zynq-7020 SoC. The stereo setup has a baseline with 46 mm and non-converged optical axis between the cameras. The cameras are configured at 1.3 Mpix @ 60 fps and distortion correction and rectification is performed in real time during image capture. With a camera resolution of 1280 pixels × 960 pixels and a maximum vertical shift of ± 20 pixels, the efficient hardware implementation utilizes 12 % of available block RAM resources.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.